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Nr5a2 is dispensable for ZGA but essential for morula development [RNA-seq]

GSE223673 Mus musculus (mouse) RNA-seq (gene expression) 514 samples Submitted 2024/07/12 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 514 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
514 samples: 38 conditions, mostly with about 10 replicates eachGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
Early embryogenesis is driven by transcription factors (TFs) that first activate the zygotic genome and then specify the lineages constituting the blastocyst. While the TFs specifying the blastocyst’s lineages are well characterised, those playing earlier roles are ill-defined. Using mouse models of the TF Nr5a2, we show that Nr5a2-/- embryos arrest at the early morula stage and exhibit overt phenotypical problems such as altered lineage specification, frequent mitotic failure and substantial chromosome segregation defects.
Read the full summary ↓
Transcriptomic profiling shows that Nr5a2 is a master regulator required for appropriate expression of thousands of genes at the 8-cells stage, including lineage-specifying TFs and genes involved in mitosis, telomere maintenance and DNA repair. We conclude that Nr5a2 coordinates proliferation, genome stability and lineage specification to ensure proper morula development.
This dataset
Open GSE223673 in finder → Find more mouse RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE223673_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA927259 and SRA study SRP418980. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
38 conditions, mostly with about 10 replicates each
E2C_mz_NrHet ×29 E2C_mz_NrKO ×22 8C_mz_DHet ×21 E2C_mz_Nrpp ×21 OoMII_NrHet ×18 E2C_m_NrKO ×18 UMI_OoMII_NrHet ×18 UMI_8C_mz_DHet ×16 +30 more

Supports a between-group comparison across 400 samples.

How we read this: 38 replicated groups read from the first 400 of 514 sample titles; they account for 400 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 474 more — browse all 514 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.